Informatica MDM Interview Questions

Informatica MDM is one of the trending technologies in the market and many companies are looking forward to hire Informatica MDM experts who have MDM skills. In case if you are going to attend an interview on Informatica MDM soon, here is a guide that clears all your roadblocks and helps you to crack the interview and acquire your dream job as Informatica MDM developer.
HRK training provides you top 30 frequently asked Informatica MDM Interview Questions 2020. This blog is packed with advanced, experienced, and entry-level questions based on the opinions of Informatica MDM specialists. Learning these frequently asked Informatica Question and Answers will increase your confidence and help you to clear the interview. 

1. Explain about MDM?

Ans: Master Data Management(MDM) is a methodology that allows the organization to link all its essential data into a single file, which is called a master file. This file seems to be a standard base reference to the organization that helps to make crucial business decisions. Master Data Management acts as a network to share the data among various firms.

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2. Tell us about the Informatica Powercenter?

Ans: Informatica Powercenter is a data integration software which is developed by Informatica Corporation. It is a widely used ETL tool (Extract, Transform, Load) to build organization data warehouses. The components of Informatica PowerCenter assists in extracting the data from multiple sources, transforming the data according to the business requirements and loading it into targeted data warehouses.

3. List out different components of Powercenter?

Ans: The following are the different components of PowerCenter: 

  • Metadata Manager
  • PowerCenter Domain
  • Repository Service
  • Administration Console
  • Integration Service
  • PowerCenter Repository Reports
  • PowerCenter Client
  • Web Services Hub
  • Data Analyzer
  • PowerCenter Repository

4. Explain to us about Data Warehousing?

Ans: The data warehouse is the primary method of managing and gathering information from various sources to assist the firms with helpful insights. Using a Data warehouse, you can analyze and integrate the data from various sources. A data warehouse is connected with different technologies and components that allow the firms to utilize the data in a well-organised process. It collects all the information in a digital form for further interpretation and moulds the data into an understandable way and makes it feasible for business users. 

5. Explain to us about various fundamental phases of data warehousing?

Ans: following are the various four fundamental phases of data warehousing. They are: 

  • Offline Operational Databases 
  • Offline data warehouse
  • Real-time data warehouse
  • Integrated data warehouse

Now, let us know about each phase of the data warehouse with useful insights. 

Offline Operational Databases: This is the initial stage of the data warehouse, evolved from copying the original operating system into an offline server. This process doesn’t impact the performance of the system. 

Offline Data Warehouse: In this phase, data warehouses update the operational data regularly such as daily, weekly, and monthly and the data is stored in an homogenous report oriented way.  

Real-time Data Warehouse: In this phase, the operating system executes an action or an event every time and updates the events in the data warehouse.  

Integrated Data Warehouse: In this last phase, data warehouses generate transactions and activities that pass through the OS, which assists the organization in daily business functionality. 

6. What are the most significant technical and management challenges in adopting MDM?

Ans: Every technical folk need to face challenges when they are selling a project and getting the funds. Management is actively looking for ROI, and they need MDM to be quantifiable advantages and profits for their business.

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7. What is meant by Dimensional Modelling?

Ans: In dimensional modelling, there are two tables which are distinct from the third normal form. In this model, fact tables used for business measurements and the dimension table contain a context. 

8. What is meant by dimension table?

Ans: Dimension table is a compilation of logic, categories, and hierarchies, which can be used for a further traverse in hierarchy nodes by a user. And the dimension table contains textual measurements stored in fact tables. 

9. Explain various methods to load the data in dimension tables?

Ans: There are two methods to load the data in dimension tables. Following are the two methods:

  • Conventional(Slow): Before storing the data into the dimension table, all constraints and keys are legalised against the data, and this process is called data integrity which is a time taking process. 
  • Direct(Fast): In this process, all constraints and keys are disabled before loading the data into the dimension table. Once loading of the information is complete into the dimension table, it validates the data against constraints and keys. In this process, if any set of data is invalid or irrelevant, then the information is skipped from the index and all future operations. 

10. Define fact tables?

Ans: In a data warehouse, a fact table consists of two columns which include metrics and measurements of business methods and foreign key. It is determined at the center of the star or snowflake schema surrounded by dimension tables.

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11. Explain the term Mapping?

Ans: Mapping represents the flow of data between the sources and targets. It is a set of target definitions and source linked by transformation objects that defines the data transformation rules. 

12. Define Mapplet?

Ans: Mapplet is a reusable element that consists set of changes that allow reusing that transformation logic in involved mappings. 

13. Explain to us about Transformation?

Ans: It is a repository element that helps to generate and modifies the data. In mapping, transformation represents certain operations that perform on integrated services. All the data that passes through these transformation ports linked with mapping. 

14. What is Data Mining?

Ans: Data Mining is the process of analysing the vast amount of data to find valuable hidden insights and compiling it into useful data. It allows the users to discover unknown relationships and patterns between various elements in the data. The useful insights extracted from the data might help you in scientific discovery, marketing, fraud detection, and many more. 

15. List out various objects that cannot be used in the Mapplets?

Ans: Following are the various objects that cannot use in the mapplets: 

  • COBOL source definition
  • Normalizer transformations
  • Joiner transformations
  • Post or pre-session stored procedures
  • sequence generator transformations that are non-reusable
  • XML source definitions
  • Target definitions
  • IBM MQ source definitions
  • Power mart 3.5 styles of Lookup functions
16. What are the foreign columns in fact and dimensional tables?

Ans: In fact table, foreign keys are the primary key of the dimensional table, and in the dimensional table, foreign keys are the primary key of the entity table.

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17. Explain different ways used in Informatica to switch one environment to another?

Ans: Following are the different ways used in Informatica to switch one environment to another:

  • By copying folder/objects
  • By exporting deploy and repository into an environment
  • By dumping every mapping to XML and using them in a new environment
  • Informatica deployment groups
18. Differentiate Mapping variables and Mapping parameters?


  • Mapping Variable: It is dynamic and changes the value during the session. The PowerCenter reads the initial value of the mapping variable and stores the value in the database after the completion of each session. And the same value is used when you run the session. 
  • Mapping Parameter: It is static, and you need to define the variable before performing the session. And this value remains the same even after completion of the session. While running the session, integration service legalises the value and keeps the same value even after the termination of the session. 
19. Explain various ways to eliminate duplicate records from Informatica?

Ans: Following are the different ways to delete the duplicate records from Informatica: 

  • By choosing the different option in the source qualifier
  • By Revoking a SQL Query in Source qualifier
  • By using Aggregator and group by all fields

20. How to find invalid mappings in a folder?

Ans: Using the following query, you can find invalid mappings in a folder:



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21. Explain different repositories that can be created using the Informatica Repository Manager?

Ans: Here are the various types of repositories that you can create in Informatica. 

  • Standalone Repository: It is a single repository that operates individually, which is not associated with other repositories. 
  • Global Repository: It is a central repository and carries shared objects over various repositories of a domain. 
  • Local Repository: Local repository stays within the domain. It can correlate to the global repository with the help of global ways and make use of these objects in their shared folders.
22. Explain different data movement modes that are available in Informatica Server?

Ans: Data movement modes provide a set of instructions to handle the process of character data. Based on that, you can determine the data movement from Informatica server configuration settings. Here are the two data movement modes:

  • ASCII Mode
  • Unicode Mode
23. Explain different types of Locks that are used in Informatica MDM 10.1?

Ans:  Following are the two types of locks used in Informatica MDM 10.1:

  • Exclusive Lock allows the individual user to access and make amends to the underlying metadata.
  • Write Lock allows various users to access and make amends to the underlying metadata at a time. 
24. List out the tools that do not require Lock-in Informatica MDM?

Ans: Following are the list of various tools that are not required lock:

  • Hierarchy Manager
  • Data Manager
  • Merge Manager
  • Audit Manager
25. List out the tools that require Lock in Informatica MDM?

Ans: Following are the tools that are required Lock to make configuration amends to the database of MDM hub master in Informatica MDM:

  • Message Queues
  • Users
  • Databases
  • Tool Access
  • Security Providers
  • Repository Manager
26. Explain about OLAP and OLTP?


  • Online Analytical Processing(OLAP) is a technology that works in the background of the application to support many business Intelligence (BI) applications. It manages, gathers and transforms multidimensional data for analysis. 
  • Online Transaction Process(OLTP) is a process that contains data and normalized tables. This application is designed to modify the data and perform day-to-day operations to analyze the data. 
27. What is the expiration module of automatic look in Informatica MDM?

Ans: For every 60 seconds the hub console is refreshed in the current situation. Lock can be released by the users manually. If a user switches to another database while the lock is on hold, the lock will be released automatically. The lock expires within a minute if the user terminates the hub console.

28. Explain various components of the Informatica hub console?

Ans: Following are the components of Informatica hub console:

  • Design Console: This element helps in configuration solution during the deployment stage and allows the changes according to the requirements in the ongoing configuration. 
  • Data Stewed Console: This element is utilised to review consolidated data and also check the data queued for the exception handling. 
  • Administration Console: This component is used to assign various database administrative activities and role-based security. 
29. List the tables that can linked to the staging date?

Ans: Following are the multiple tables that can integrate with the staging data in MDM. They are:

  • Raw Table
  • Staging Table
  • Landing Table
  • Rejects Table

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30. Tell us about various loading phases in MDM?

Ans: Following are the various stages in which data is stored into hub stores in a sequential process.

  • Land
  • Stage
  • Load
  • Match
  • Consolidate

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As a senior Technical Content Writer for HKR Trainings, Gayathri has a good comprehension of the present technical innovations, which incorporates perspectives like Business Intelligence and Analytics. She conveys advanced technical ideas precisely and vividly, as conceivable to the target group, guaranteeing that the content is available to clients. She writes qualitative content in the field of Data Warehousing & ETL, Big Data Analytics, and ERP Tools. Connect me on LinkedIn.